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Updated: Jan 6, 2026

Evaluation of Photosynthetic Behaviors by Simultaneous Measurements of Leaf Reflectance and Chlorophyll Fluorescence Analyses
Published on: August 9, 2019
Photochemical reflectance index and its relation to photosynthetic characteristics under dynamic light environment
Jing-Qi Zhang1, Kouki Hikosaka1, Hajime Tomimatsu1
1Graduate School of Life Sciences, Tohoku University, 6-3, Aoba, Aramaki, Aoba, Sendai 980-8578, Japan.
Abstract:
The photochemical reflectance index (PRI) is a normalized reflectance index that is expected to be useful for estimating photosynthetic activity based on remote-sensing images. Experimental and theoretical studies have examined how the PRI is related to photosynthesis, but they have been based on observations under steady-state light conditions. Photosynthetic systems display differential temporal responsiveness when exposed to variation in light intensity. Here, we examined the responses of the CO2 assimilation rate (A), quantum yield of PSII photochemistry (ФP), nonphotochemical quenching (NPQ), and the PRI in two poplar species, one being a hybrid that does not close stomata in the dark (nonclosing type). When dark-adapted leaves were exposed to strong light (induction phase), the response time was ФP = NPQ < PRI < A for the normal type and ФP = NPQ < PRI = A for the nonclosing type. Consequently, the PRI-NPQ and the PRI-A relationships differed between the steady-state and induction phase. On the other hand, when the light-adapted leaves were transferred from dark to light, the time response was similar among ФP, NPQ, and the PRI. Therefore, the PRI can be used to assess ФP and NPQ even under dynamic light conditions if light-adapted leaves are used. Our results imply that, following sudden increases in light intensity, CO2 assimilation in the normal type poplar is limited by stomatal conductance, and that PSII-related parameters, including the PRI, are temporally decoupled from A. Estimates of A based on the PRI would be overestimates under dynamic conditions, which needs to be taken into account when interpreting remote-sensing data.
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